mirror of
https://github.com/graphdeco-inria/gaussian-splatting
synced 2024-11-22 00:08:02 +00:00
118 lines
4.3 KiB
Python
118 lines
4.3 KiB
Python
# Copyright 2021 The PlenOctree Authors.
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# 1. Redistributions of source code must retain the above copyright notice,
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# this list of conditions and the following disclaimer.
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#
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# 2. Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
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# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.
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import torch
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C0 = 0.28209479177387814
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C1 = 0.4886025119029199
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C2 = [
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1.0925484305920792,
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-1.0925484305920792,
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0.31539156525252005,
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-1.0925484305920792,
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0.5462742152960396
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]
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C3 = [
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-0.5900435899266435,
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2.890611442640554,
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-0.4570457994644658,
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0.3731763325901154,
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-0.4570457994644658,
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1.445305721320277,
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-0.5900435899266435
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]
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C4 = [
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2.5033429417967046,
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-1.7701307697799304,
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0.9461746957575601,
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-0.6690465435572892,
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0.10578554691520431,
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-0.6690465435572892,
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0.47308734787878004,
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-1.7701307697799304,
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0.6258357354491761,
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]
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def eval_sh(deg, sh, dirs):
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"""
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Evaluate spherical harmonics at unit directions
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using hardcoded SH polynomials.
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Works with torch/np/jnp.
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... Can be 0 or more batch dimensions.
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Args:
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deg: int SH deg. Currently, 0-3 supported
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sh: jnp.ndarray SH coeffs [..., C, (deg + 1) ** 2]
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dirs: jnp.ndarray unit directions [..., 3]
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Returns:
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[..., C]
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"""
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assert deg <= 4 and deg >= 0
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coeff = (deg + 1) ** 2
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assert sh.shape[-1] >= coeff
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result = C0 * sh[..., 0]
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if deg > 0:
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x, y, z = dirs[..., 0:1], dirs[..., 1:2], dirs[..., 2:3]
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result = (result -
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C1 * y * sh[..., 1] +
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C1 * z * sh[..., 2] -
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C1 * x * sh[..., 3])
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if deg > 1:
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xx, yy, zz = x * x, y * y, z * z
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xy, yz, xz = x * y, y * z, x * z
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result = (result +
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C2[0] * xy * sh[..., 4] +
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C2[1] * yz * sh[..., 5] +
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C2[2] * (2.0 * zz - xx - yy) * sh[..., 6] +
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C2[3] * xz * sh[..., 7] +
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C2[4] * (xx - yy) * sh[..., 8])
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if deg > 2:
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result = (result +
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C3[0] * y * (3 * xx - yy) * sh[..., 9] +
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C3[1] * xy * z * sh[..., 10] +
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C3[2] * y * (4 * zz - xx - yy)* sh[..., 11] +
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C3[3] * z * (2 * zz - 3 * xx - 3 * yy) * sh[..., 12] +
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C3[4] * x * (4 * zz - xx - yy) * sh[..., 13] +
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C3[5] * z * (xx - yy) * sh[..., 14] +
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C3[6] * x * (xx - 3 * yy) * sh[..., 15])
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if deg > 3:
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result = (result + C4[0] * xy * (xx - yy) * sh[..., 16] +
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C4[1] * yz * (3 * xx - yy) * sh[..., 17] +
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C4[2] * xy * (7 * zz - 1) * sh[..., 18] +
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C4[3] * yz * (7 * zz - 3) * sh[..., 19] +
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C4[4] * (zz * (35 * zz - 30) + 3) * sh[..., 20] +
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C4[5] * xz * (7 * zz - 3) * sh[..., 21] +
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C4[6] * (xx - yy) * (7 * zz - 1) * sh[..., 22] +
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C4[7] * xz * (xx - 3 * yy) * sh[..., 23] +
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C4[8] * (xx * (xx - 3 * yy) - yy * (3 * xx - yy)) * sh[..., 24])
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return result
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def RGB2SH(rgb):
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return (rgb - 0.5) / C0
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def SH2RGB(sh):
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return sh * C0 + 0.5 |